Blood pressure (BP) measurements in childhood and young adulthood are less predictive of future levels than those taken in middle age. In part, this may be due to the fact that within-person variability appears to make up a larger proportion of total variability in childhood than adulthood. Our previous work on an NHLBI supported grant has indicated that repeated BP measurements and visits lead to higher childhood tracking correlations over a period of 3 years. We propose to use data on the same cohort of 339 children (ages 8-15 at entry), who have been followed for 9-12 years, to extend our analyses of BP tracking to a period that spans childhood and young adulthood. The follow-up data also include multiple visits which will reduce the large within-person variability of BP measurements and improve the tracking correlations. In addition, we will provide "true" or "corrected" tracking correlations by eliminating the effects of random measurement error. We will examine the effect of time-varying covariates on both the observed and true tracking correlations. Besides computing tracking correlations, we intend to compute predictive values for young adult BP given childhood levels. This is the probability that a young adult's true BP is above a specific cutpoint conditional on childhood BP. These values will be validated using data from the Fels Longitudinal Study, which includes serial BP measurements over the age range in our study. The prediction models will also be derived including terms for covariates such as age, sex, height and weight. From these models nomograms can be constructed which would be useful to physicians for prognostic purposes. Thus, because of the unique multiple-visit approach used in these data, we can eliminate the effect of random measurement error, and make statements about an individual's true underlying blood pressure. These methodologic improvements may strengthen the usefulness of BP screening in childhood to detect those at high risk of developing hypertension.